提升复杂系统的定量决策支持，将成本作为独立变量（CAIV）寻求“最佳”点设计，是一个约束的非线性优化问题，其目标函数是最优有效性度量（MOE）表示，由基于性能的成本模型、二阶约束MOEs、系统性能指标的界限（MOPs）构成。算法采用的是同时扰动随机逼近方法（SPSA）。附件中是二阶约束MOEs模型的仿真程序。附：仿真流程图-Ascend the quantitative decision support of complex systems, will cost as an independent variable (CAIV), look for the \"best\" design is a constrained nonlinear optimization problem, the objective function is the optimal effectiveness measures (MOE), said by a cost model based on performance, second-order constraints, the boundaries of MOEs, system performance index (MOPs). Algorithm USES a method perturbation stochastic approximation (SPSA) at the same time. Attached is a quadratic constraint MOEs simulation program of the model.